1. Field of the Invention
The present invention relates to page decomposition and more particularly to a method of page decomposition using local orthogonal transforms and a map optimization.
2. Discussion of Related Art
Despite the emergence of electronic documents there has not been a significant decrease in the use of paper based documents. In fact, The use of paper documents may have increased due to a preference for paper documents for reading and archiving purposes. Similarly, newspapers continue to be popular even after the introduction of the radio, TV and World Wide Web. However, storing and analyzing paper documents and more importantly, retrieving them can be a cumbersome task. Electronic documents however, have the advantage that they can be manipulated and analyzed easily. Consequently, transformation of a paper document to an electronic form has become an important task.
The understanding and transformation of paper documents is nontrivial. It has been observed that the development of a general system that can process all kinds of documents such as technical reports, engineering drawings, books, journals, newspapers etc. can be far more complex. For coding and understanding a range of documents, an application needs to identify text, image and graphics regions as physical segments of the page to be able to process them properly.
The majority of page segmentation works are, to an extent, dependent on page layout and can be classified as either bottom-up or top-down. Bottom-up approaches often use connected component grouping where one starts from the pixel level and, in an hierarchical fashion, combines pixels into larger and larger entities such as characters, lines, text, graphics etc. In the top-down strategy, an image is broken into blocks that can be identified and further subdivided appropriately. There are also hybrid methods that combine the top-down and the bottom-up approaches. In other approaches, after detecting major blocks, simple statistical tests classify them as either text or non-text regions. Black pixel density, black/white ratio, transitions, average vertical or horizontal run-lengths are some of the features that these methods take into account during post classification stages. Yet another method analyses the background white space. In this scheme, major white spaces between printed components are tracked to identify boundaries. This method is based on a few assumptions and provides good results even for skewed images or documents with complex layouts. However, it can only be applied for images that are clean and where there is no overlap between regions.
In contrast to the geometric layout analysis, the logical layout analysis has not received as much attention. Some logical analysis performs region identification or classification in a derived geometric layout. These approaches are however, primarily rule based and thus the final outcome depends on the dependability of the prior information and how well that is represented within the rules.
Therefore, a need exists for a method of page decomposition using local orthogonal transforms and a map optimization.